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International Journal of Bioelectromagnetism
Vol. 5, No. 1, pp. 340-341, 2003.

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Myocardial Infarction in Body Surface Potential Mapping; Temporal and Spatial Analysis of the Depolarization Wave

Paula Vesterinena, Helena Hänninena, Milla Karvonend, Kirsi Lauermac, Miia Holmströmc, Markku Mäkijärvia, Jukka Nenonend, Toivo Katilad, and Lauri Toivonena

aDivision of Cardiology, bBioMag Laboratory, and cDepartment of Radiology, Helsinki University Central Hospital; Helsinki, Finland
dLaboratory of Biomedical Engineering, Helsinki University of Technology; Espoo, Finland


Abstract. We studied the ability of different time segments of the depolarization wave recorded with body surface potential mapping (BSPM) to detect and localize myocardial infarction. BSPM was recorded in 24 patients with remote myocardial infarction, localized with magnetic resonance imaging (MRI), and in 24 healthy controls. The depolarization wave was divided into six temporally equal segments and time integral values for the segments were calculated. The time segments of the depolarization wave showed different infarction detection capability depending on infarction location. Time segment analysis of the QRS deflection offers potential to improve detection and localization of old myocardial infarction.

Keywords:   Body Surface Potential Mapping; Myocardial Infarction; Magnetic Resonance Imaging; Depolarization; Time Integral

1.    Introduction

The left ventricular depolarization in a normal heart begins in the septum, spreads to the apex and anterior left ventricular wall from endo- to epicardial direction. Finally the depolarization wave spreads to the basal regions of the heart (1). We hypothetized that electrocardiographic abnormalities of old myocardial infarctions manifest at different time segments of the QRS deflection depending on the locality of the infarction.

2.    Materials and Methods

The study population consisted of 24 patients with angiographically verified coronary artery disease (CAD) and a history of one or more remote myocardial infarctions, and 24 healthy volunteers. Resting BSPM with 120 unipolar leads covering the whole thorax was recorded for 5 minutes. The localization and extent of the infarcted myocardium was determined by combined method of cine MRI and contrast enhanced MRI, which was used as a reference method (2). The myocardium was divided into eight segments, which were in agreement with the American Heart Associations (AHA) recommendation of left ventricular segmentation (3), and patients were grouped into five groups according to their infarction location.

QRS was divided into six temporally equal segments, referred to as sextiles. The QRS time integral and corresponding discriminant indices (DI), calculated as described by Kornreich et al (4), were determined for each patient group within each sextile. DI was used to identify the optimal recording locations to separate a patient group from the control group.

3.    Results

For the anterior infarction (Table) the time integral performance was best during the early QRS. Characteristic was the decrease in time integral values as compared to controls over most of the anterior thorax. This change was more pronounced on the right side of the thorax.

For the lateral infarction the time integral performed best during the first half of the QRS and then quickly deteriorated. Characteristic was the increase in time integral values over most of the anterior thorax in the very beginning of the QRS complex as compared to the controls. Then the time integral values began to decrease, as compared to the controls, on the right side of the thorax.

For the inferior infarction the time integral performed best during the early mid phase of the QRS and then deteriorated. Characteristic was a decrease in time integral values, as compared to controls, over the mid-inferior part of the anterior thorax.

For the posterior infarction the time integral performance was at its best during the mid phases of the QRS with increasing performance towards the later mid phase. Decreased time integral values, as compared to controls, were found over the inferior part of the anterior chest.

For the apical infarction the performance profile was increasing from the early mid phase towards the early final phase of QRS.

Table 1.    Optimal time segment and optimal location for detecting infarction.

Infarction

Optimal sextile

Optimal location

Number of leads with [DI]>1 in optimal sextile

Number of leads with p-value < 0.05 in optimal sextile

Anterior

2nd

right inferior

21

37

Lateral

1st

left 4th intercostal area

31

28

Inferior

3rd

mid inferior

32

58

Posterior

4th

left inferior

12

25

Apical

5th

right superior

17

48

4.    Discussion

We found that the ability to detect infarction is different for various QRS time segments depending on the location of the infarction. We recognized characteristic performance profile for the sextiles of the depolarization wave for each infarction location. These findings of peak detection performance timing within the QRS complex are roughly in agreement with the known sequence of the distribution of the depolarization wave in the heart (1), except for the late apical detection.

The optimal leads for infarction detection of each infarction site lie outside the standard 12-lead ECG. The localization of remote myocardial infarction can be improved by time integral analysis of different segments of QRS deflection and by choosing optimal leads for each suspected infarction location.

Acknowledgements

This work was supported by Finnish Cardiac Research Foundation, Aarne Koskelo Foundation, Academy of Finland, Paulo Foundation, and Helsinki University Central Hospital Research Funds

References

1. Surawicz B. Spread of activation in the heart. In: Electrophysiologic basis of ECG and cardiac arrhythmias. Williams & Wilkins, 1995: 257-267.

2. Lauerma K, Niemi P, Hänninen H et al. Multimodality MR imaging assessment of myocardial viability: Combination of first-pass and late contrast enhancement to wall motion dynamics and comparison with FDG PET-Initial experience. Radiology 2000; 217: 729-736.

3. Cerquiera MC, Weissman NJ, Dilsizian V et al. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. Circulation 2002; 105: 539-542.

4. Kornreich F, Montague TJ, Rautaharju P. Identification of first acute Q wave and non-Q wave myocardial infarction by multivariate analysis of body surface potential maps. Circulation 1991; 84: 2442-2453.

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